4.7 Article

Accurate parameter estimation for star formation history in galaxies using SDSS spectra

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1111/j.1365-2966.2009.15349.x

关键词

methods: data analysis; methods: numerical; galaxies: evolution; galaxies: formation; galaxies: stellar content

资金

  1. NSF [CCF-0625879, DMS-0707059, N00014-08-1-0673.]
  2. Alfred P. Sloan Foundation
  3. National Science Foundation,
  4. U.S. Department of Energy
  5. National Aeronautics and Space Administration,
  6. Japanese Monbukagakusho
  7. Max Planck Society
  8. Higher Education Funding Council for England
  9. CNPq
  10. CAPES
  11. FAPESP
  12. France-Brazil CAPES/Cofecub

向作者/读者索取更多资源

To further our knowledge of the complex physical process of galaxy formation, it is essential that we characterize the formation and evolution of large data bases of galaxies. The spectral synthesis starlight code of Cid Fernandes et al. was designed for this purpose. Results of starlight are highly dependent on the choice of input basis of simple stellar population (SSP) spectra. Speed of the code, which uses random walks through the parameter space, scales as the square of the number of the basis spectra, making it computationally necessary to choose a small number of SSPs that are coarsely sampled in age and metallicity. In this paper, we develop methods based on a diffusion map that, for the first time, choose appropriate bases of prototype SSP spectra from a large set of SSP spectra designed to approximate the continuous grid of age and metallicity of SSPs of which galaxies are truly composed. We show that our techniques achieve better accuracy of physical parameter estimation for simulated galaxies. Specifically, we show that our methods significantly decrease the age-metallicity degeneracy that is common in galaxy population synthesis methods. We analyse a sample of 3046 galaxies in Sloan Digital Sky Survey Data Release 6 and compare the parameter estimates obtained from different basis choices.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据